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The Journal of Neuroscience, November 15, 1999, 19(22):10044-10052
Gaze Direction Modulates Finger Movement Activation Patterns in
Human Cerebral Cortex
Justin T.
Baker1,
John
P.
Donoghue1, and
Jerome N.
Sanes1, 2
1 Department of Neuroscience, Division of Biology and
Medicine, Brown University, Providence, Rhode Island 02912, and
2 Scientific Institute Santa Lucia, 00179 Rome, Italy
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ABSTRACT |
We investigated whether gaze direction modified the pattern of
finger movement activation in human cerebral cortex using functional magnetic resonance imaging (MRI). Participants performed a sequential finger-tapping task or made no finger movements while maintaining gaze
in the direction of the moving hand (aligned conditions) or away from
the location of the moving hand. Functional MR signals, measured
in the hemisphere contralateral to the moving hand, revealed finger
movement-related activation in primary motor cortex, lateral and medial
premotor cortex, and a wide extent of the lateral superior and inferior
parietal lobules. In each area, the extent of the finger movement
activation increased when static gaze was more aligned with the moving
hand compared to when gaze was directed away from the moving hand.
These data suggest the existence of large-scale cortical networks
related to finger actions and indicate that skeletomotor processing in
the cerebral cortex is consistently modified by gaze direction signals.
Key words:
functional magnetic resonance imaging; voluntary hand
movement; eye position; motor cortical networks; cerebral cortex; oculcomotor-skeletomotor interactions
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INTRODUCTION |
In humans, accurate goal-directed
reach and grasp movements typically rely on foveal vision (Jeannerod et
al., 1992 ). Ongoing registration of visual percepts with gaze and limb
positioning would seem imperative to accomplish this behavior. How
these processes evolve within the cerebral cortex is emerging from
recent neurophysiological and neuroimaging studies. Neurons in
occipital, parietal, and frontal lobes of monkeys change their sensory
or motor response properties according to gaze direction, limb
position, or alignment with other sensory modalities (Andersen et al.,
1990 ; Fogassi et al., 1992 ; Boussaoud et al., 1993 , 1998 ; Galletti et
al., 1993 ; Graziano et al., 1994 ; Boussaoud, 1995 ; Mushiake et
al., 1997 ; Trotter and Celebrini, 1999 ). In addition, a number of
interconnected regions of cortex can show functional labeling when
humans perform tasks requiring concurrent mapping of oculomotor and
skeletomotor space (Iacoboni et al., 1997 ).
Understanding cortical mechanisms of visually guided movement requires
identifying brain sites that register visual and motor information.
Visual (Felleman and Van Essen, 1991 ) and motor processing (Rao et al.,
1993 ; Sanes et al., 1995 ) both engage broad areas of cerebral cortex,
but it is less clear how these signals become integrated across the
cerebral cortex or subcortical areas for visually guided actions and
object manipulation (Wise et al., 1997 ). Based on recordings in
monkeys, visual information within the cortex first appears to be
integrated with oculomotor, head, and body representations in posterior
parietal cortex (Andersen et al., 1990 ; Duhamel et al., 1992 , 1998 ;
Johnson et al., 1996 ; Batista et al., 1999 ). Neurons in posterior
parietal cortex alter their response to visual stimuli depending on
gaze direction (Andersen et al., 1990 ; Duhamel et al., 1992 , 1997 ) and
to limb and head position (Graziano et al., 1994 ), indicating that
baseline motor states influence properties of multimodal sensory
neurons. Projection patterns from parietal lobe to frontal motor
cortical areas (Luppino et al., 1993 ; Tanné et al., 1995 ; Johnson
et al., 1996 ; Matelli et al., 1998 ) suggest that this visual motor
integration proceeds in parallel across several parietal and frontal
regions at once. In support of this view, Graziano et al. (1994)
described neurons in the ventral portion of macaque lateral premotor
cortex (PMA) that are responsive to both visual and somatic sensory
stimuli and also have stable responses when gaze shifts (Graziano and Gross, 1998 ), indicating that these neurons code in an extraretinal coordinate system. By contrast, gaze angle modifies the directional tuning of arm-related neurons in dorsal PMA when monkeys prepared to
reach (Boussaoud, 1995 ; Boussaoud et al., 1998 ). Additionally, Mushiake
et al. (1997) found similar results for ventral PMA while monkeys
moved, but gaze sensitivity did not occur for the sampled neurons in
primary motor cortex (MI). Thus, gaze interactions occur for the monkey
in several areas ordinarily believed linked to arm movement processing.
Similar to the situation in monkey, multiple arm movement-related areas
exist in human cortex. However, the direct influence of gaze on
movement-related activity in human cortex has not been investigated.
Consequently, we used functional neuroimaging techniques to investigate
gaze direction effects on the level of activation in human cortex
produced by sequential finger movements.
Parts of this paper have been published previously (Sanes et al.,
1996 ).
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MATERIALS AND METHODS |
Participants. Eleven healthy normal volunteers (aged
20-35 years; six female, five male) were recruited from the Brown
University and Beth Israel Deaconess Medical Center communities. All
were right-handed as determined by a handedness survey that required participants to rate hand usage preferences for nine common functions, using the choices among always left, usually left, no preference, usually right, and always right. Each item was scored on an integer scale ranging from 2 (corresponding to "always left") to +2
(corresponding to "always right") to yield total scores between
18 and + 18. The group mean score (±SEM) was 15.8 ± 0.47, indicating a strong right-handed group tendency. Participants continued
in the study after successful screening for contraindications such as
bodily ferromagnetic objects and absence of general health problems. Before magnetic resonance imaging (MRI), participants were instructed and trained in the behavioral tasks. All participants gave written informed consent, according to established Institution Review Board
guidelines at Brown University and Beth Israel Deaconess Medical Center
(Boston, MA; the site of MRI) for human participation in experimental procedures.
Apparatus. A 1.5 T Vision Magnetom MR system (Siemens
Medical Systems, Erlangen, Germany) equipped for echoplanar imaging was
used for acquiring anatomical and functional MR images. Participants lay supine on a transport for insertion into the MRI system bore with
the head resting within a circularly polarized head coil that was used
for radio frequency transmission and reception. The nasion was aligned
with a laser cross-hair projection, so that each participant's head
would be approximately centered in the standing magnetic field of the
MR system once within the MR bore. Head movement was minimized by mild
restraint and cushioning.
MRI. After shimming the standing magnetic field to account
for inhomogeneities introduced by the participant, we acquired a
three-dimensional T1-weighted anatomical data set [Siemens MPRAGE; repetition time (TR), 10 msec; echo time (TE), 64 msec; inversion time
(TI), 20 msec; 1 mm isotropic voxels] for off-line registration with
functionally active sites. Functional MR images were acquired in an
axial plane roughly parallel to the body of the corpus callosum using
blood oxygenation level-dependent imaging (Kwong et al., 1992 ) that
provides an MR signal likely related to local, aggregate neuronal
processing. With this method, physiological changes in the oxygenation
state of hemoglobin were used to produce functional maps of brain
activation during finger movements. Using a 240 × 360 mm field of
view with a 1282 sampling matrix, six or
eight 8-mm-thick slices were sampled in a region from the superior
convexity to about the level of the inferior frontal sulcus to yield
voxels with in-plane resolution of 2.81 × 1.875 mm2 and a volume of 31.6-42.2
mm3. The imaging sequence used a TR of 2 sec and TE of 64 msec. The choice of six or eight slices was based on
practical and theoretical considerations. The practical considerations
related to limitations of the MR system when the MR data were obtained.
From a theoretical perspective, the sampling space covered the arm
areas of frontal motor areas (Rao et al., 1993 ; Sanes et al.,
1995 ) and would also have been expected to sample the appropriate arm
movement-related regions of parietal cortex.
Procedures. Functional MR images were obtained while
participants alternately performed sequential finger movements or
participated in a no-movement condition. The sequential finger
movements consisted of finger tapping with the right hand in which the
tip of each finger was touched in succession to the tip of the thumb at
a rate of two touches per second. This movement rate was chosen to
elicit robust yet discrete activation patterns across frontal and
parietal motor areas of the cerebral cortex (Sadato et al., 1996 ;
Schlaug et al., 1996 ). All movements were performed while the
participant lay supine with the supinated right arm at the right side
of the body. During a no-movement condition, participants lay still,
maintained the same arm posture without making any finger movements,
and fixed gaze in the instructed direction without thinking of or
making any finger movements.
For both the movement and no-movement conditions, participants fixed
gaze in one of three directions: leftward 10-15°, central, or
rightward 10-15° (Fig.
1A). Before MRI, the
experimenter assessed each participant's ability to deviate and to
maintain gaze by ~10-15° without rotating the head and to perform
sequential finger movements repetitively at 2 Hz for 30 sec. Once
transported into the MR system bore, participants fixed gaze using
self-selected visual cues on the illuminated ceiling of the bore.
Although the experimenters visually monitored each participant's hand
movements from the MR control room, no quantitative measures of
movement characteristics were obtained. Nevertheless, all participants complied with the instructions and performed the movement task according to continual visual inspection by the experimenters and gaze
deviation by a postimaging interview.

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Figure 1.
Experimental design. A, Schematic
indicating the arm (bottom right) positioned at the
right side of a participant, an expected activation in the
contralateral hemisphere in motor areas (note area in opaque
white in the vicinity of the central sulcus as demarcated by
the two outlined triangles), and the three directions of
gaze performed separately. B, Time and event lines
indicating alternation of no-movement and finger movements for
successive 30 sec periods for a total of 5-6 min for each gaze
direction. See Materials and Methods for additional details and gaze
terminology.
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Sequences of successive 30 sec functional MRI measurements were
obtained during the movement and no-movement conditions (Fig. 1B). A 5-6 sec pause intervened between each
condition. A repeating series of movement and no-movement conditions
occurred for each direction of gaze. During each 30 sec movement or
no-movement condition, 15 functional MR images were obtained for each
of the sampled slices. MR data were obtained continuously for 15-18
min during which four or five alternations of 30 sec of the movement and no-movement conditions occurred for each of the three gaze directions. To account for nuisance variables that may have affected the functional MR signal, such as attention, habituation of the functional MR signal related to finger movement, and other global variables, the ordering of gaze direction was counterbalanced across
participants. During the pauses between conditions, participants were
verbally instructed about the direction of gaze to achieve and whether
or not to move the fingers. For the four initial participants, an
additional movement condition of repetitive 2 Hz index finger flexion
and extension, interleaved among the other conditions, was included
along with the sequential finger movement and no-movement conditions.
These data are not considered in this report.
Data analysis. UNIX workstations were used for data
processing and to create digital representations of the structural and functional MR data. For analysis and visualization, AVS 5.0x (Advanced Visual Systems, Inc., Waltham, MA) was used with a combination of
supplied and custom-made processing modules.
We analyzed MR signals occurring in both hemispheres and initially
processed the data obtained during each of the three gaze directions
independently. The first two volumetric acquisitions were discarded
because of MR signal overshoot leaving 13 data points per 30 sec epoch
for subsequent analysis and a total of 104 data points for each of
three separate analyses (leftward, central, and rightward gaze). The
remaining time series of functional MR signal intensity for each voxel
in the left hemisphere was correlated with a boxcar reference function
to identify differences in MR signal between the movement and
no-movement conditions (Fig. 1B; Bandettini et al.,
1993 ). The boxcar reference function cannot readily detect possible
response decrements occurring across the 30 sec movements blocks.
However, qualitative inspection of the data did not indicate
substantial response decrements across the movement periods. The
counterbalanced design used for gaze direction across participants (see
Procedures) controlled for possible interactions between gaze direction
and response decrement. We used a probability threshold of
p 0.01 to identify voxels exhibiting increases in
functional MR signal during finger movements in comparison to
no-movement. To protect against type I statistical errors, we used a
Bonferroni correction using the total number of voxels in the areas
selected for analysis a priori. Across participants, the
number of voxels in the regions assessed for a gaze effect on finger
movement representations ranged from 3156 to 4896, and these numbers
were used to correct the p value for each participant. The
corrected p values (0.01/number of pixels × three
comparisons) ranged from p = 0.34-0.53 × 10 7 to yield corrected r
values from 0.46 to 0.47. We used r = 0.46 as the
threshold to identify labeled voxels for all comparisons.
The correlation analysis yielded r maps with thresholded
voxels for each gaze direction, hereafter referred to equivalently as
label, activation, or the motor representation for a particular gaze
direction. For localization of functional sites, the r maps were superimposed onto the three-dimensional structural MR images. We
used the individual patterns of cerebral cortical gyri and sulci to
determine the anatomic location of labeling (Kretschmann and Weinrich,
1986 ; Talairach and Tournoux, 1988 ) in five predefined regions of
cerebral cortex; although for two regions we assessed MR label
bilaterally. Figure 2A
illustrates the general location of these cerebral cortical regions,
and Figure 2B depicts how they were defined on two
horizontal slices of a single participant's brain. First, a region
that likely corresponds to MI (Brodmann area 4; BA4); this region
includes the posterior half of the precentral gyrus, from the fundus of
the central sulcus to its lateral surface on each slice. The
delineation of MI was straightforward, because the central sulcus was
identifiable in MR images from all participants. A second cortical area
that we term the lateral premotor area (PMA) likely corresponds to
lateral BA6 or homologously PMd of the monkey. PMA includes the
anterior half of the precentral gyrus immediately rostral to MI, and
the gray matter immediately anterior to the precentral sulcus but not
including cortex at the intersection of precentral and superior frontal
sulci. Third, the medial frontal gyrus posterior to the vertical
anterior commissure line (Talairach and Tournoux, 1988 ) and anterior to
the paracentral lobule that likely corresponds to the posterior
portions of medial BA6, that has commonly been termed supplementary
motor area (SMA). For MI, PMA, and SMA, the sampled region extended
from the topmost slice (at or near the superior convexity) to the
bottommost slice with activation, although for SMA the lowest slice did
not encroach on the cingulate gyrus. Fourth, the superior parietal
lobule (SPL) encompassed cortex medial to the interparietal sulcus,
including cortex on the medial wall of the interparietal sulcus,
posterior to the postcentral sulcus, anterior to the
parietal-occipital sulcus, and lateral to regions around sulci
communicating with the central fissure. SPL likely included BA5 and
lateral portions of BA7. Fifth, a region we termed the inferior
parietal lobule (IPL) that likely encompassed portions of BA39 and BA40
within the angular and supramarginal gyri. The borders of IPL included the interparietal sulcus medially and superiorly, the
occipital-parietal sulcus posteriorly and inferiorly (maximally,
depending on the sampling extent) when the Sylvian fissure begins to
curve superiorly in its anterior-to-posterior course, and the
postcentral sulcus anteriorly. MR label in MI and SMA was assessed in
both hemispheres, but was assessed only in the contralateral, left
hemisphere for PMA, SPL, and IPL because of our judgment of
insufficient (from statistical sampling perspectives) labeling in the
ipsilateral hemisphere for these three regions.

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Figure 2.
Cerebral cortical regions assessed and exemplar
activation patterns. A, B, Color-coded
illustration of the cortical regions assessed for functional MR
activation. MI in red, PMA in green, SMA
in purple, SPL in orange, and IPL in
yellow. See Materials and Methods for additional details
of sulcal and gyral landmarks defining each region. VAC,
Vertical plane through the anterior commissure perpendicular to a line
between the anterior and posterior commissures; VPC,
vertical plane through the posterior commissure perpendicular to a line
between the anterior and posterior commissures. C,
Functional MR labeling in two exemplars, slice obtained from a single
participant (slice planes indicated on whole brain volumes at right).
The least activation occurred for leftward gaze, whereas that for both
central and rightward gaze exceeded that for leftward gaze. The images
with overlain label depict mostly portions of the left, contralateral
hemisphere (L, left; R, right).
Red arrowhead indicates fundus of central sulcus
(indicated by green lines).
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Using software sketching tools for each participant individually, we
outlined each cortical region on the relevant slices of functional MR
data using the anatomical data as guides. We checked the outlining by
comparing parasagittal and horizontal slices using gyral and sulcal
anatomy relative to a given region. When a regional border was manually
drawn onto a slice of the structural MR image, statistical data
characterizing the activation patterns found within that cortical
region were obtained for all gaze directions to ensure common regional
sampling for each gaze direction. The number of labeled voxels within a
cortical region was used as the primary dependent variable for
subsequent analyses, although we also obtained MR signal intensity data
(see below). Using regression and other inferential statistical
methods, the voxel counts were analyzed to assess how gaze direction
influenced activation related to finger movements.
In a subsidiary analysis to determine additional aspects of the MR
activation pattern, we measured the functional MR signal intensity of
activated voxels only within contralateral MI (MIc) and contralateral
SMA (SMAc). This analysis was restricted to MIc and SMAc again because
of our judgment of small sample sizes in ipsilateral MI (MIi) and
ipsilateral SMA (SMAi). For this analysis, we operationally classified
voxels as being "gaze-dependent" or "gaze-independent"
according to the observations of activation or no-activation of
individual voxels. MR signal intensity changes across gaze directions
were considered (see below) after making this classification.
Independently for MIc and SMAc, the movement-related activation that
occurred for leftward gaze became the reference for defining
gaze-dependent or gaze-independent voxels. A voxel was classified as
gaze-dependent if it had above-threshold MR signal for only one or two
gaze directions. By contrast, gaze-independent voxels exhibited greater
than baseline MR signal in relation to finger movements for all three
gaze directions. We inspected the anatomical distribution of
gaze-dependent and gaze-independent voxels. For each voxel, we also
calculated the mean percentage increase of functional MR signal for the
movement versus the no-movement condition and then compared these
values between gaze-dependent and gaze-independent voxels using ANOVA
methods. Furthermore, we compared the MR signal intensities for
gaze-dependent and gaze-independent voxels obtained during the
no-movement condition. Additionally, MR signal intensity was compared
across the three gaze directions, to distinguish between two competing
models of the cortical response.
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RESULTS |
Anatomic distribution of activation
Labeling occurred in aggregates most typically containing two or
more contiguous voxels distributed primarily across the contralateral, left parietal, and frontal lobes, although labeling also occurred in
ipsilateral cortex, particularly in MIi and SMAi. The labeled aggregates were often spatially segregated, even within presumed cytoarchitechtonic fields, to yield a patchy general activation pattern. For example, Figure 2C illustrates the distribution
of functional activation obtained from one participant who exhibited typical functional MR labeling occurring in frontal and parietal cortex
during finger movements.
Finger movement yielded labeled voxels in the left, and to a lesser
extent the right, hemisphere when participants directed gaze toward at
least one location for all 11 participants (Table 1). Activation occurred in MIc for all
participants when gaze was directed to at least one location.
Activation of contralateral PMA (PMAc), SMA, SPL (SPLc), and IPL (IPLc)
occurred as frequently as that for MIc, although with fewer activated
voxels, as will be noted below.
Activation in MIc was typically distributed across several slices
within each individual. We used the intersection of the fundus of the
superior frontal sulcus and the precentral sulcus as an anatomic
landmark to assess the superior-inferior extent of MIc labeling. All
participants exhibited activation at this junction, and 9 of 11 exhibited label on both the slices superior and inferior to this sulcal
intersection. Thus, most participants had MIc label spanning 18-24 mm
in the superior-inferior dimension. The distribution of labeled voxels
in MIc along the mediolateral dimension was not uniform across
participants. However, qualitative inspection of the data indicated
that MI activation typically occurred just lateral to the fundus of the
central sulcus and extended about half-way toward the lateral surface
of the gyrus. Labeling in MIi was sparser, on average about one-eighth
the number of activated voxels in comparison to MIc (see quantification below).
Labeling in PMAc, SMAc SMAi, SPLc, and IPLc also occurred in patchy
patterns with separate small aggregates of activated voxels or even
single voxels interspersed within the borders of each region (Fig.
2C). Aggregates of label in PMAc typically distributed along
the anterior precentral gyrus and its various branches, most commonly
located at or around the intersection of the precentral and superior
frontal sulci. In most cases, PMAc activation extended laterally along
the anterior half of the precentral gyrus toward the lateral surface.
Label in SMAc or SMAi extended over a relatively small area and
typically encompassed a single voxel cluster or a few scattered voxels
across one or two slices. Activation in IPLc and SPLc most commonly
occurred immediately posterior to the postcentral sulcus and in the
gray matter, either superior or inferior to the interparietal sulcus.
Areal activation and gaze modulation
The amount of cortical label varied with brain area and gaze
direction. Across the gaze directions, participants exhibited the
largest areal activation in MIc (79.5 ± 7.1; p 0.0001; mean of participant means ± SEM; all gaze directions
combined). The number of activated voxels decreased progressively for
SMAc (22.6 ± 5.6), PMAc (20.45 ± 7.88), IPLc (17.48 ± 3.77), SPLc (16.0 ± 2.82), MIi (10.4 ± 2.5), and SMAi
(6.5 ± 3.0). For MIc, MIi, SMAc, and SPLc, all 11 participants
exhibited the greatest amount of MR label during either central or
rightward gaze (Table 2), with no
participant having the greatest activation for leftward gaze in these
areas. Although leftward gaze yielded fewer activated voxels, it
occasionally resulted in more activated voxels than central or
rightward gaze across the sampled cortical regions (Table 2,
Left, numbers in parentheses). For PMAc, SMAi, and IPLc, only one participant, although different for the three areas, exhibited the greatest activation for leftward gaze. Across the group
of participants and brain areas, the regional volume of movement-related activation obtained during leftward gaze was always
less than that obtained during either central or rightward gaze
( 2 13.2; p 0.0005). A similar analysis comparing the regional activation volumes
between central and rightward gaze revealed that only MIi showed a
group difference in activation for these two directions
(p 0.05; central < rightward). However,
this effect in MIi accounted for only 15% of the variance and would be
considered statistically weak.
Figure 3 illustrates the group results of
labeled voxel counts by gaze condition for each cortical region. We
quantified the effect of gaze direction on the area of functionally
activated cortex by performing a regression analysis including gaze
direction, cortical region, and participant as nominal factors and the
number of voxels as a continuous dependent variable. The overall
regression analysis revealed a main effect of gaze direction on brain
activation (p 0.0001). Subsequent analyses
statistically verified that activation area increased significantly for
central and rightward gaze relative to leftward gaze
(p 0.05). We found no difference in the
number of activated voxels observed when comparing central and
rightward gaze (p > 0.05). A power analysis
indicated a least significant number of >42 million to approach a
significant difference between central and rightward gaze at
p 0.05. Qualitative inspection of the grouped data
suggested that gaze direction differentially affected the amount of
labeling across cortical areas, but this interaction effect did not
reach statistical significance. A power analysis of these data
indicated a least significant number of >600,000 to reach a
significant gaze direction by area interaction at p 0.05. Subsidiary analyses also revealed that five of the seven cortical
areas assessed exhibited significant changes in areal activation
related to gaze direction. An absence of a significant main effect of
gaze direction on finger movement-related activation occurred only in
SMAi (p = 0.07; power analysis indicated that increase in observations from 33 to 37 observations would likely achieve a p 0.05), and IPLc
(p = 0.23; power analysis indicated a needed
increase from 33 to 67 observations).

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Figure 3.
Functional activation. The number of activated
voxels in each analyzed brain region for each direction of gaze. All
areas exhibited the least amount of activation for leftward gaze.
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A further aspect of the maximal areal activation concerns the across
region congruence of labeling (Table 3).
In addition to the observation that participants exhibited the greatest
areal activation for one gaze direction, we found that the activation pattern within a participant could have substantial across-region congruence in cerebral cortex contralateral to the finger movements regarding the direction of gaze that yielded the greatest activation. Figure 2C illustrates this effect qualitatively for a single
participant who exhibited the greatest total activation while directing
gaze centrally. In analyzing these data quantitatively, we found that MIc, SMAc, PMAc, and SPLc exhibited statistically significant congruencies for all possible between-area pairs across participants. IPLc exhibited this type of congruence pattern for MIc, SMAc, PMAc, but
not for SPLc. MIi and SMAi did not exhibit regional congruence for
maximal activation in a gaze direction. Across hemispheres, MIc and
PMAc exhibited congruence with SMAi, but not with MIi, whereas SPLc
exhibited congruence with MIi but not SMAi. In summary, 9 of 10 of the
paired comparisons between contralateral cortical areas reached
statistical significance (Table 3; 2 = 14.72; p 0.0001). In comparison to the congruence of
the gaze effect across regions in contralateral cortex, six of nine of
these between-area comparisons across the hemispheres did not reach
statistical significance ( 2 = 2.04;
p > 0.05).
Gaze dependency of functional MR labeling
General characteristics and anatomic distribution
To determine whether the anatomic distribution of gaze-dependent
voxels differed from those of gaze-independent voxels, we qualitatively
inspected sets of images depicting the relative locations of the two
voxel types across the left hemisphere. Figure 4 shows data from two participants,
indicating no clear anatomic segregation of voxels with gaze-dependent
activation from those with gaze-independent activation in MIc, PMAc, or
SMAc or the parietal lobe areas examined. Across all areas, the numbers
of gaze-independent voxels were small but tended to be largest in MIc
and SMAc. Thus, we decided to restrict subsequent analysis of
properties of gaze-independent and gaze-dependent voxels to MIc and
SMAc. In MIc, all 11 participants exhibited gaze-dependent and
gaze-independent voxels. For SMAc, all 11 participants had gaze-dependent voxels, and 8 of 11 had gaze-independent voxels, although an additional two of these eight participants had <10 gaze-independent voxels.

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Figure 4.
Spatial distribution for gaze-independent and
gaze-dependent voxels. Exemplar activation patterns from two
participants (one slice each in left and right
panels), illustrating the intermixing of gaze-independent and
gaze-dependent voxels across brain regions. Voxels indicated in
white correspond to gaze-independent, and those in
black correspond to gaze-dependent. White
triangle indicates the interparietal sulcus; white
triangle with a black outline indicates SMAc;
black triangle with white outline
indicates MIc.
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Model of gaze modulation
How gaze direction affected finger movement-related activation
might be explained by considering two competing models (Fig. 5). For both models, we have assumed that
the labeled voxels, along with a larger population of subthreshold
voxels, comprise a Gaussian distribution of MR signal intensity. For
the leftward gaze task, the labeled voxels occur within the central,
above-threshold portion of the total voxel distribution (Fig. 5,
left). The relative increase of the activation volume during
central and rightward gaze could have resulted either from an expansion
effect (Fig. 5, center) or an increase in the height or gain
effect (Fig. 5, right) of the response function. Both
effects would yield more suprathreshold voxels. However, the resulting
average suprathreshold MR signal would differ between the two possible
effects, with the expansion effect yielding little change or a decrease
in average suprathreshold MR signal, whereas the gain effect must yield
an increase in suprathreshold MR signal. Figure 5 (center)
illustrates that for the expansion effect, only the voxels on the tails
of the label distribution would exhibit MR signal increase. In
contrast, a gain effect predicts that all labeled voxels would show
increased MR signal (Fig. 5, right) for central and
rightward gaze. Empirical data can distinguish between these two
possible models of how gaze modulates movement-related MR signal, but
only if the labeled voxels form two classes; gaze-dependent and
gaze-independent voxels (see Materials and Methods for definitions of
this classification).

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Figure 5.
Model of gaze-independent and gaze-dependent
voxels. Hypothetical distributions of MR signal intensity for the
sampled voxels for different gaze directions. The
leftmost distribution represents MR signal obtained
during leftward gaze. The voxels passing the statistical criteria for
identification as "activated" would fall between the two
horizontal dashed lines and exhibit the highest MR
signal intensity for the entire distribution. The center
and rightmost distributions represent possible response
functions that could explain the observed data, with the dashed
lines remaining as that for leftward gaze. Additional details
in Results.
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MR signal intensity
Collapsed across all gaze directions, the percentage increase in
functional MR signal related to finger movement was greater for
gaze-independent than for gaze-dependent voxels
(p 0.005, data not shown, but apparent from
Fig. 6). Analysis of the individual M1c
data revealed that all 11 participants exhibited a higher percentage
functional MR signal change for gaze-independent voxels than that
observed for the gaze-dependent voxels (p values < 0.01). For the six participants with >10 gaze-independent voxels in
SMAc, the obtained percentage functional MR signal change was greater for gaze-independent than for gaze-dependent voxels
(p values < 0.01). The mean functional MR
signal obtained during the no-movement condition did not differ between
gaze-independent and gaze-dependent voxels in M1c and SMAc (data not
shown).

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Figure 6.
Gaze-related MR signal intensity. The percentage
increase in movement-related (vs no-movement) in MR signal intensity is
illustrated for MIc (A) and SMAc
(B) for each of the gaze directions and for the
two classes of activated voxels; gaze-dependent and gaze-independent.
No differences in MR signal were observed for the gaze-independent
voxels in either MIc or SMAc. By contrast, MR signal obtained from
labeled voxels in MIc and SMAc in increased for the gaze-dependent
voxels when participants looked in a sector of visual space that
yielded more active voxels.
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|
An analysis of functional MR signal intensity using gaze direction and
voxel type (independent or dependent) as nominal factors indicated that
the percentage increase in functional MR signal for gaze-dependent
voxels differed between leftward and central gaze
(p 0.05; Fig. 6, left). This
finding has consistency with the model of both expansion and gain
effects. By contrast, MR signal did not differ across gaze directions
for the gaze-independent voxels (Fig. 6, right), nor did
gaze direction affect the baseline MR signal (data not shown). Taken
together, these findings have consistency with the expansion model of
the cortical response function.
 |
DISCUSSION |
The current results indicate that gaze direction modulates
movement-related activation in frontal and parietal cortex. We found
that the greatest activation occurred while participants directed gaze
either centrally or rightward to the hemisphere controlling the
movement. Moreover, the gaze direction for which an individual
exhibited the greatest activation remained congruent across several
cortical regions, suggesting existence of coordinated neuronal networks
spanning parietal and frontal lobes to register eye and hand movements.
In contrast, MR signal intensity was only marginally affected by gaze
direction. Neither the baseline MR signal nor the relative increase of
MR signal occurring during movements varied with gaze position. Along
with other behavioral and neurophysiology results (Boussaoud, 1995 ;
Mushiake et al., 1997 ; Boussaoud et al., 1998 ; Henriques et al., 1998 ),
the present data suggest that gaze direction is a salient variable for
the neural systems controlling hand motor actions and that changes in
gaze likely modify activation patterns dynamically and instantaneously.
Gaze modulation in cerebral cortex
The mechanisms for gaze modulation in cerebral cortex have not
been completely determined, although recent neurophysiology recordings
in monkeys provide clues as to how gaze direction could modify the
activity in distributed neuronal populations (Andersen, 1995 ;
Boussaoud, 1995 ; Mushiake et al., 1997 ; Boussaoud et al., 1998 ).
Andersen (1995) has proposed that neurons in parietal cortical area BA
7a combine visual and gaze signals to form planar gain fields. Visual
responses of these cells vary linearly with horizontal and vertical eye
position, with the maximal neural response occurring when eye position
and the most responsive part of its visual field are aligned. Although
similar mechanisms have not been described in frontal motor areas,
evidence exists suggesting the gaze can modify the arm direction coding
of neurons in the dorsal and ventral portions of monkey premotor cortex
(Boussaoud, 1995 ; Mushiake et al., 1997 ; Boussaoud et al., 1998 ). In
combination, the data on gaze effects on visual and arm motor
representations may suggest that gaze direction could dramatically and
dynamically change movement representations for the arm and hand at the
level of large neuronal populations.
The current data and work obtained from neural recordings in monkeys
indicate that changes in gaze direction can modify response properties
in several frontal and parietal areas. In monkeys, gaze can have
regular and predictable effects on neuronal activity across visual
space, as for the planar gaze fields for parietal neurons (Andersen,
1995 , Bremmer et al., 1999 ). Alternatively, the effect of gaze on
directional tuning of neurons can vary widely across individual neurons
and not yield a population response, indicating a particular
gaze-induced bias, as observed in PMA (Boussaoud et al., 1998 ) and the
ventral intraparietal area (Bremmer et al., 1999 ). Our data indicate
similarity of the gaze effect across parietal and frontal regions, but
it remains uncertain whether similar mechanisms generated these effects
in each area. Perhaps analogous to directional tuning for neurons in
sensory and motor systems, although surely on a widely different scale, we found that each participant possessed a "preferred" gaze
direction to modulate activation related to finger movements, and this
preferred direction had consistency across several anatomically linked
brain regions. Although this preference differed across participants, a
seemingly consistent bias on motor processing existed within each
participant, perhaps functioning to exert a concerted effect on
multiple stages of sensory motor processing.
The inter-regional congruence of the general gaze effect across
parietal and cortical areas may reflect operation of a coordinated neural network that plans movements in an eye-centered reference frame.
These findings suggest but do not provide adequate details or confirm
existence of such a network. Recent work has indicated that neurons in
a posterior parietal region appear to code for reaching in an
eye-centered coordinate framework (Batista et al., 1999 ), although
these data may bear more on reaches to targets under direct visual
guidance; a situation not studied in the current work. Connections from
the SPL, likely including the parietal reach region to frontal premotor
areas of monkeys (Johnson et al., 1996 ; Wise et al., 1997 ; Matelli et
al., 1998 ), may provide an anatomical substrate for the common gaze
effects on finger movements that we observed. Our data provide evidence
of gaze modulation of finger movement in diverse motor-related areas, but the results do not indicate the precise role that gaze has in each
of these cortical areas, nor do the results bear upon important gaze
and skeletomotor processes mediated by subcortical structures.
Nevertheless, the parietal reach region and nearby arm movement-related
zones may have mechanisms that use gaze direction to help mediate
visual motor coordinate transformations processed, in part, in
posterior parietal areas (Johnson et al., 1996 ). In the frontal
premotor areas, gaze direction may affect the final stages of motor
planning, whereas in MI gaze direction may have a modulatory role in
regulating ongoing movement. Further experiments will be needed to
determine the specific role of gaze direction on human brain
representation of finger movements.
Another point to consider concerns the spatial compatibility between
gaze direction and the finger movements. Greater PET activation occurs
bilaterally in SPL when visual stimuli are processed in the hemisphere
opposite to that used for a motor response, an "incompatible"
stimulus-response condition, compared to a "compatible" stimulus-response condition (Iacoboni et al., 1996 ). A parsimonious interpretation of these data relates to enhanced processing required for resolving stimulus-response incompatibilities with respect to
primary brain processing sites. In the current work, both hemispheres received information about the static visual target as compared to
lateralized visual input used previously (Iacoboni et al., 1996 ).
However, the current tasks may have oculomotor and skeletomotor compatibility or incompatibility, with leftward gaze having spatial incompatibility whereas central and rightward gaze have spatial compatibility with the movement. Because greatest activation occurred for spatially compatible gaze and finger movement, it would seem that
there exist differences between sensory-motor (Iacoboni et al., 1996 )
and motor-motor mappings.
Gaze effect is not a general processing effect
Evidence from neuropsychology suggests that spatial processing in
humans is asymmetrical; the right hemisphere may be capable of
performing spatial operations in both visual hemifields, whereas the
left hemisphere is equipped for operations restricted to the right side
of space (Perenin and Vighetto, 1988 ). Therefore, it is possible that
rightward gaze engages a left hemisphere spatial processing system in a
general sense. However, our data regarding baseline MR signal intensity
do not support general processing biases during rightward gaze. MR
signal intensity did not vary with gaze position during the no-movement
task, suggesting that the gaze modulation is specific to conditions of movement.
Another potential confound in our data could be the effect of selective
spatial attention on the activation extent. Various researchers have
proposed that the attentional shifts may use the same neuronal
populations involved in oculomotor behaviors (Kustov and Robinson,
1996 ). Furthermore, under normal conditions, attention is typically
attached to the fovea and thus is directed in the same direction as
gaze position. An alternative interpretation of the current results
that could explain the changes in activation patterns with shifts in
gaze would be a shifting of attentional focus that accompanied gaze
changes. Whereas we cannot readily distinguish attentional from gaze
effect, Corbetta et al. (1998) have described common sites of
activation for attentional and oculomotor tasks, making such
distinctions even more difficult in humans. However, other neuroimaging
studies in humans have noted increases in MR signal intensity with
added attention (O'Craven et al., 1997 ); a finding consistent with the
gain effect but inconsistent with the expansion effect in our model of
the observed cortical responses. Furthermore, if attention had overall
salience for the results, we might have expected that gaze direction
would have also affected the functional MR signal, not only the number of activated voxels, during the movement and no-movement tasks. This
generalized elevation did not occur. Thus, we believe that the observed
areal expansions in cortical motor representations with gaze shifts are
more related to interactions between oculomotor and motor systems than
to global attentional biases.
General conclusions
The major finding of this study indicates that gaze direction
modulates the spatial extent of the movement-related activation pattern
in the human cerebral cortex. Three main results emerge from analyzing
functional activation occurring within multiple cortical regions while
participants performed repetitive right-handed finger movements and
fixed gaze leftward, central, or rightward. First, gaze direction
modulates the activation amount during simple right-handed finger
movements across multiple regions of human cerebral cortex. Second, the
extent of functional MR label is greatest when participants direct gaze
to the hemisphere contralateral to the movement. Third, sites showing
activation for all gaze conditions exhibit different patterns of MR
signal intensity from sites having gaze-selective activation. Although
the mechanisms underlying these changes remain unknown, we propose that
the rapid gaze-induced changes may indicate that neurons involved in
controlling a finger movement can be dynamically modulated by input
from oculomotor systems. Furthermore, this modulation may reflect
increases in the processing demands of the motor system that occur when
spatial signals are potentially available to guide actions. Thus, the current work upholds the suggestion from neurophysiology that spatial
information contributes to motor control processes in the primate brain.
 |
FOOTNOTES |
Received Nov. 24, 1998; revised July 26, 1999; accepted Aug. 24, 1999.
This work was supported by National Institutes of Health Grants AG10634
(J.N.S.), NS35376 (J.N.S.), NS25074 (J.P.D.), and the James S. McDonnell Foundation (J.N.S.).
Correspondence should be addressed to Dr. Jerome N. Sanes, Department
of Neuroscience, Brown University, Box 1953, Providence, RI 02912. E-mail: Jerome_Sanes{at}Brown.edu.
J.T. Baker's present address: Department of Anatomy and Neurobiology,
Washington University School of Medicine, 660 South Euclid Avenue, St.
Louis, MO 63110.
 |
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